Dynamic
Systems Control Laboratory
The Engine Control Research Laboratory at UH focuses on research, education and technology transfer aspects involving the regulations, optimization, control, monitoring and diagnostics of internal combustion engine and power train systems with the overall objective of optimizing their economy and harmful emission reduction.
Developing controller design methodologies that generate production-intent engine controllers for low emissions, improved fuel economy and optimal performance. This includes simplified controller calibration processes (desktop calibration), improved performance and guaranteed robustness.
*Engineering desktop and data driven tools for (a) multivariable controller design, (b) linear/nonlinear robust controller design, (c)gain scheduling controller design, and (d) self-calibrating controllers.
*Multivariable control for loop cooperation in multi-objective engine air handling applications.
*Optimal integration of the engine, exhaust aftertreatment systems, and powertrain.
*Engine/aftertreatment diagnostics & prognostics using information synthesis and simplified models.
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Dynamic
Systems Control Laboratory |
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—————————————————————————————————————————————— Laboratory Overview—————————————————————————————————————————————— The DSCL at the University of Houston is involved in the analytical, numerical and experimental aspects of controlled dynamic systems, that is, systems that include feedback to enable and improve their response. Feedback controlled dynamic systems are encountered in numerous engineering applications, such as, engines, space systems, active vibration isolation systems, manufacturing processes, petrochemical processes and bioengineering systems. The increasing complexity, dimensionality and performance demands on modern controlled systems present new challenges in the control design and the determination of optimized closed-loop performance that often encompasses multiple conflicting objectives. Novel multivariable analysis and design methods that compensate for system complexity, variability, nonlinearities and system delays are investigated. In addition, system identification, prognostics/diagnostics and health monitoring approaches are examined to determine appropriate mathematical modeling and on-line or off-line conditioning of a system. A specific focus of the DSCL is the investigation of Failure -Tolerant Intelligent Structural Systems (FTISS). Intelligent Structural Systems (ISS) are structures which integrate control and computational subsystems into a single structural entity. Ideally, ISS adapt their dynamic characteristics to meet performance objectives at any instant. FTISS in addition integrate the likelihood of control component and structural member failure in both the off-line and on-line control/structure design process. The need for FTISS is critical for complex and interconnected dynamic systems such as underwater vehicles, bridges and buildings, high-altitude powered platforms and satellites/space structures which are required to operate unattended for extended periods of time and/or are too intricate for human operators to discern problems.To realize this potential, however, advances are needed in several technical areas, including the development and modelling of embedded sensor/actuators and material subsystems, algorithms for control/adaption, techniques for FTISS health monitoring, integrated approaches for system design accounting for the likelihood of component failure, and efficient techniques for both off-line numerical simulation and real-time implementation. |
